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  1. 1
    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost

    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

    Published 2024
    “…PSO-EBGWO is used to optimize the parameters of the CatBoost model. …”
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  2. 2
    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
    “…Therefore, test data generation for t-way testing need to be optimized. Many t-way test data generation strategies have been proposed in the literature to generate optimized t-way test data. …”
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  3. 3
    TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm

    TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm by Kamal Z., Zamli, Alsariera, Yazan A.

    Published 2016
    “…This project develops a novel strategy to minimize the test consideration using the Particle Swarm Optimization and the Bat Algorithm.…”
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  4. 4
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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  5. 5
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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  6. 6
    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…The AFW algorithm reduces unnecessary computations by focusing only on useful edge entries in the graph, thereby expediting the optimization process. …”
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  7. 7
    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm

    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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  8. 8
    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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  9. 9
    Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review

    Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

    Published 2024
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  10. 10
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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  11. 11
    Mobile data gathering algorithms for wireless sensor networks

    Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

    Published 2014
    “…The third proposed algorithm achieves an adaptive data gathering strategy. …”
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  12. 12
    Identification of continuous-time hammerstein model using improved archimedes optimization algorithm

    Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

    Published 2024
    “…Although various optimization algorithms have been widely employed in multiple applications, the traditional Archimedes optimization algorithm (AOA) has presented imbalanced exploration with exploitation phases and the propensity for local optima entrapment. …”
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  13. 13
    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller

    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

    Published 2010
    “…The performance of GA can be further improved by using different combinations of selection strategies, crossover and mutation methods, and other genetic parameters such as population size, probability of crossover and mutation rate. …”
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  14. 14
    Development of efficient t-way test data generation algorithm and execution strategies

    Development of efficient t-way test data generation algorithm and execution strategies by Khandakar Fazley, Rabbi

    Published 2012
    “…This strategy is able to reduce the number of test data, but the execution time is not optimized. …”
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  15. 15
    Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm

    Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm by Li, Man, Liu, Fang, Abdullah, Zulhamri

    Published 2024
    “…This model uses multichannel convolution feature, BN and Dropout strategy to promote performance for the model. Secondly, this work designs optimization measures from inertia weight and learning factor to build an improved particle swarm optimization algorithm (IPSO). …”
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  16. 16
    Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying

    Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

    Published 2019
    “…The parameter dependency problem of the off-line and on-line model is handled with QPSO and new meta-cognitive learning strategy, respectively. …”
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  17. 17
    Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm

    Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm by Danzomo, Bashir A., Salami, Momoh Jimoh Eyiomika, Khan, Md. Raisuddin

    Published 2015
    “…This includes the use of an artificial neural network (ANN) based predictive control strategy and differential evolution (DE) optimization algorithm to determines the optimal control signal, uk (liquid droplet size, dD) by minimizing the cost function such that the output is set below the allowable PM concentration. …”
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  18. 18
    Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks

    Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks by Al-Humairi, Ali Zuhair Abdulameer

    Published 2009
    “…This thesis proposes an optimized strategy namely cross-layer design in routing algorithms used find the best route for all SSs and scheduling algorithms, used to assign a time slot for each possible node transmission. …”
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  19. 19
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
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  20. 20
    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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